scholarly journals Multivariate Analysis of the Effect of Climate Conditions on Gold Production in Ghana

2018 ◽  
Vol 18 (1) ◽  
pp. 72-77
Author(s):  
Sampson Takyi Appiah ◽  
Albert Buabeng ◽  
N. K. Dumakor-Dupey
Keyword(s):  
Time Series ◽  
Regression Models ◽  
Relative Effect ◽  
Climatic Conditions ◽  
Standard Errors ◽  
Climate Factors ◽  
Gold Production ◽  
Planning And Scheduling ◽  
Climate Conditions ◽  
Production Planning And Scheduling

The change in climatic conditions and its catastrophic effect on mining activities has become a source of worry for mining industries and therefore needs due attention. This study examined the effect some climate factors have on gold production in Ghana. First, a direct Multiple Linear Regression was applied on the climate factors with the aim of determining the relative effect of each factor on gold production which exhibited a time series structure. The consequence is that, the estimates of the coefficients and their standard errors will be wrongly estimated if the time series structure of the errors is ignored. In order to eliminate these deficiencies and better understand the effect of these climate factors on gold production, regression with ARIMA errors technique was employed after its appropriateness has been tested. The model was then compared in terms of prediction accuracy which resulted a MAPE of 9.78%. It was concluded that, gold production in Ghana is positively related to Temperature whilst negatively to Rainfall and Precipitate. It was recommended that mine operators in Ghana could base on this analysis to optimise their production planning and scheduling. Keywords: Gold Production, Climate, Multicollinearity, VIF, Regression Models with ARIMA Errors

Impact of basin-wide dry climate conditions and non-climatic drivers: an isolation approach

2016 ◽  
Vol 7 (3) ◽  
pp. 498-513 ◽  
Author(s):  
Furat A. M. Al-Faraj ◽  
Miklas Scholz
Keyword(s):  
Water Resources ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
River Regulation ◽  
Relative Effect ◽  
Climatic Conditions ◽  
Climate Conditions ◽  
Decision Making Processes ◽  
Diyala River ◽  
The Standardized Precipitation Index

The sustainable management of water resources subjected to the joined influence of transboundary basin-wide dry climatic conditions and intensive man-made river regulations in an upper riparian state on the stream flow regime of a downstream country is a serious challenge. This is particularly the case for arid and semi-arid regions where water resources are limited. The Diyala river basin, shared between Iraq and Iran, was used as an example. The study aims to develop a generic approach to isolate the relative effect of upstream man-made interventions from the mutual impacts of basin-wide dry climate environments and upstream human-induced pressures. The proposed method supports water managers in unbiased, timely and spatially relevant decision-making processes. The streamflow drought index and the monthly-based truncation level were utilized to characterize hydrological droughts, while the standardized precipitation index was used for meteorological drought interpretations. Findings revealed that the upstream river regulation schemes noticeably led to a decline in water availability of the downstream country. The relative impact ranged from a minimum value of 5% in February to the highest value of 54% in July. The average proportional impacts between April and October and between November and March were about 46% and 17%, respectively.

scholarly journals Association between Climatic Conditions, Population Density and COVID-19 in Indonesia

2021 ◽  
Vol 50 (3) ◽  
pp. 879-887
Author(s):  
AZIZAH R. ◽  
SANTI MARTINI SANTI MARTINI ◽  
LILIS SULISTYORINI LILIS SULISTYORINI ◽  
MAHMUDAH MAHMUDAH ◽  
ADITYA SUKMA PAWITRA ◽  
...  
Keyword(s):  
Population Density ◽  
Air Temperature ◽  
Virus Disease ◽  
Climatic Conditions ◽  
Cluster Method ◽  
Tropical Region ◽  
Climate Factors ◽  
Climate Conditions ◽  
Exact Test ◽  
Populated Region

The first emergence of Corona Virus Disease 2019 (COVID-19) confirmed cases found in Wuhan, China, has become a global crisis. At least 177 countries have been affected over 43,000,000 confirmed cases of corona positive and more than one million deaths until October 27th, 2020. Recent research has analyzed any possible factors causing the COVID-19 spreads were climate factors and population density. Indonesia was a tropical region known as the high-populated country in the World, with a 52.9% area with a high mean air temperature and over 267.7 million populations. Our study aims to analyze the correlation between climate, population density, and COVID-19 in Indonesia. We used the K-means cluster method and Fisher’s exact test to determine climatic conditions, population density, and COVID-19 clusters and study the correlation. Our research found that there is a correlation between climatic conditions and population density with COVID-19 (p: 0,034; p:0,004). Warmer climate conditions and densely populated regions contributed to the risen COVID-19 transmission in Indonesia. These are highlighted by the evidence of the top six provinces with highest COVID-19 cases are province classified in warmer climatic conditions (high air temperature, low rainfall, and humidity) and a fairly-dense to densely populated region.

scholarly journals ROLE OF CLIMATE IN PRACTICE OF PANCHAKARMA: A CRITICAL REVIEW

2021 ◽  
Vol 12 (1) ◽  
pp. 96-100
Author(s):  
Hemant . ◽  
Shreyas DM ◽  
Kiran M Goud
Keyword(s):  
Healthy Person ◽  
Climatic Conditions ◽  
The Other ◽  
Climate Factors ◽  
Climate Classification ◽  
Direct Role ◽  
Climate Conditions ◽  
Köppen Climate Classification ◽  
Moderate Climate

Ayurveda is a science of life focusing not only to cure the Rogi but also towards the maintenance of the health of a healthy person. Panchakarma is a modality giving a variety of opportunities to fulfill the main aim of Ayurveda. There are lots of factors which are involved to certainly administer therapy in such a way that it will always be infallibly effective. Among all those factors climate or Kala is one of the factors which influences almost every aspect in one way or the other. Today the Koppen Climate classification gives us the background to understand the climatic conditions in various places. These climate conditions will occur according to the Desha also, so Desha plays a direct role in influencing the Kala factor as Six seasons are not to be found everywhere around the globe. This variation of the seasons makes difficult for the physician to apply the concepts of Ritu and Shodhana accordingly for e.g., a place like Bengaluru has a moderate climate all over year yet being near to equator as compare to other cities in Karnataka because of the height from seas level. Therefore, an understanding of comparing the current seasons of cities based on distance from equator, height from sea level with the Sadharana and Asadharana Ritu for commencing the Sukhatama Vamanadi Karma is needed. Therefore, an attempt is made to describe the entire possible climate factors which play a role in commencing the Panchakarma therapies effectively.

Ecological specificities of the interaction between animal breeding and climate changes, caused by greenhouse gas emissions

2017 ◽  
Vol 4 (3) ◽  
pp. 62-72
Author(s):  
O. Zhukorsky ◽  
O. Nykyforuk ◽  
N. Boltyk
Keyword(s):  
Greenhouse Gases ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Climatic Conditions ◽  
Animal Breeding ◽  
Gas Emissions ◽  
Climate Conditions ◽  
Emissions Inventory ◽  
Theoretical Substantiation ◽  
Global Problems

Aim. Proper development of animal breeding in the conditions of current global problems and the decrease of anthropogenic burden on environment due to greenhouse gas emissions, caused by animal breeding activity, require the study of interaction processes between animal breeding and external climatic conditions. Methods. The theoretical substantiation of the problem was performed based on scientifi c literature, statistical informa- tion of the UN Food and Agriculture Organization and the data of the National greenhouse gas emissions inventory in Ukraine. Theoretically possible emissions of greenhouse gases into atmosphere due to animal breeding in Ukraine and specifi c farms are calculated by the international methods using the statistical infor- mation about animal breeding in Ukraine and the economic-technological information of the activity of the investigated farms. Results. The interaction between the animal breeding production and weather-and-climate conditions of environment was analyzed. Possible vectors of activity for the industry, which promote global warming and negative processes, related to it, were determined. The main factors, affecting the formation of greenhouse gases from the activity of enterprises, aimed at animal breeding production, were characterized. Literature data, statistical data and calculations were used to analyze the role of animal breeding in the green- house gas emissions in global and national framework as well as at the level of specifi c farms with the consid- eration of individual specifi cities of these farms. Conclusions. Current global problems require clear balance between constant development of sustainable animal breeding and the decrease of the carbon footprint due to the activity of animal breeding.

scholarly journals Relationship between Relative Maturity and Grain Yield of Maize (Zea mays L.) Hybrids in Northwest New Mexico for the 2003–2019 Period

Agriculture ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 290
Author(s):  
Koffi Djaman ◽  
Curtis Owen ◽  
Margaret M. West ◽  
Samuel Allen ◽  
Komlan Koudahe ◽  
...  
Keyword(s):  
New Mexico ◽  
Grain Yield ◽  
Sprinkler Irrigation ◽  
Growing Season ◽  
Climatic Conditions ◽  
Agricultural Science ◽  
Production Optimization ◽  
Science Center ◽  
Early Season ◽  
Climate Conditions

The highly variable weather under changing climate conditions affects the establishment and the cutoff of crop growing season and exposes crops to failure if producers choose non-adapted relative maturity that matches the characteristics of the crop growing season. This study aimed to determine the relationship between maize hybrid relative maturity and the grain yield and determine the relative maturity range that will sustain maize production in northwest New Mexico (NM). Different relative maturity maize hybrids were grown at the Agricultural Science Center at Farmington ((Latitude 36.69° North, Longitude 108.31° West, elevation 1720 m) from 2003 to 2019 under sprinkler irrigation. A total of 343 hybrids were grouped as early and full season hybrids according to their relative maturity that ranged from 93 to 119 and 64 hybrids with unknown relative maturity. The crops were grown under optimal management condition with no stress of any kind. The results showed non-significant increase in grain yield in early season hybrids and non-significant decrease in grain yield with relative maturity in full season hybrids. The relative maturity range of 100–110 obtained reasonable high grain yields and could be considered under the northwestern New Mexico climatic conditions. However, more research should target the evaluation of different planting date coupled with plant population density to determine the planting window for the early season and full season hybrids for the production optimization and sustainability.

scholarly journals Correlation between Acinetobacter baumannii Resistance and Hospital Use of Meropenem, Cefepime, and Ciprofloxacin: Time Series Analysis and Dynamic Regression Models

Pathogens ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 480
Author(s):  
Rania Kousovista ◽  
Christos Athanasiou ◽  
Konstantinos Liaskonis ◽  
Olga Ivopoulou ◽  
George Ismailos ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Acinetobacter Baumannii ◽  
Regression Models ◽  
Tertiary Care ◽  
Antimicrobial Use ◽  
Care Hospital ◽  
Arima Models ◽  
Series Analysis ◽  
Resistance Rates

Acinetobacter baumannii is one of the most difficult-to-treat pathogens worldwide, due to developed resistance. The aim of this study was to evaluate the use of widely prescribed antimicrobials and the respective resistance rates of A. baumannii, and to explore the relationship between antimicrobial use and the emergence of A. baumannii resistance in a tertiary care hospital. Monthly data on A. baumannii susceptibility rates and antimicrobial use, between January 2014 and December 2017, were analyzed using time series analysis (Autoregressive Integrated Moving Average (ARIMA) models) and dynamic regression models. Temporal correlations between meropenem, cefepime, and ciprofloxacin use and the corresponding rates of A. baumannii resistance were documented. The results of ARIMA models showed statistically significant correlation between meropenem use and the detection rate of meropenem-resistant A. baumannii with a lag of two months (p = 0.024). A positive association, with one month lag, was identified between cefepime use and cefepime-resistant A. baumannii (p = 0.028), as well as between ciprofloxacin use and its resistance (p < 0.001). The dynamic regression models offered explanation of variance for the resistance rates (R2 > 0.60). The magnitude of the effect on resistance for each antimicrobial agent differed significantly.

scholarly journals A Weighted-Time-Lag Method to Detect Lag Vegetation Response to Climate Variation: A Case Study in Loess Plateau, China, 1982–2013

2021 ◽  
Vol 13 (5) ◽  
pp. 923
Author(s):  
Qianqian Sun ◽  
Chao Liu ◽  
Tianyang Chen ◽  
Anbing Zhang
Keyword(s):  
Climate Change ◽  
Loess Plateau ◽  
Time Lag ◽  
New Method ◽  
Climate Factors ◽  
The Loess Plateau ◽  
Climate Conditions ◽  
Vegetation Growth ◽  
Lag Effect

Vegetation fluctuation is sensitive to climate change, and this response exhibits a time lag. Traditionally, scholars estimated this lag effect by considering the immediate prior lag (e.g., where vegetation in the current month is impacted by the climate in a certain prior month) or the lag accumulation (e.g., where vegetation in the current month is impacted by the last several months). The essence of these two methods is that vegetation growth is impacted by climate conditions in the prior period or several consecutive previous periods, which fails to consider the different impacts coming from each of those prior periods. Therefore, this study proposed a new approach, the weighted time-lag method, in detecting the lag effect of climate conditions coming from different prior periods. Essentially, the new method is a generalized extension of the lag-accumulation method. However, the new method detects how many prior periods need to be considered and, most importantly, the differentiated climate impact on vegetation growth in each of the determined prior periods. We tested the performance of the new method in the Loess Plateau by comparing various lag detection methods by using the linear model between the climate factors and the normalized difference vegetation index (NDVI). The case study confirmed four main findings: (1) the response of vegetation growth exhibits time lag to both precipitation and temperature; (2) there are apparent differences in the time lag effect detected by various methods, but the weighted time-lag method produced the highest determination coefficient (R2) in the linear model and provided the most specific lag pattern over the determined prior periods; (3) the vegetation growth is most sensitive to climate factors in the current month and the last month in the Loess Plateau but reflects a varied of responses to other prior months; and (4) the impact of temperature on vegetation growth is higher than that of precipitation. The new method provides a much more precise detection of the lag effect of climate change on vegetation growth and makes a smart decision about soil conservation and ecological restoration after severe climate events, such as long-lasting drought or flooding.

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